In contact centers, one of the primary benefits of using an automated dialing device (e.g., a predictive dialer) to place outbound calls is the ability for such a device to screen out unproductive calls, or at least a portion of them, without having to involve agents. That is to say, an automated dialing device is able to ascertain the difference between live parties and answering machines or voice mail services answering calls and can “screen out” such calls, thus only passing calls that have been answered by live parties to agents. Accordingly, this allows agents to spend more time speaking with their intended parties and as a result dramatically increases the overall productivity of the contact center. Such “call screening” capabilities are generally referred to as “call progress analysis.”
However, the use of automated dialing devices is generally not recommended for business-to-business (“B2B”) environments because of the current call progress analysis capabilities of such devices in detecting machines and services. This is because a large majority of business phone systems answer calls using some type of automation such as an auto attendant (e.g., interactive voice response system—“IVR”) or hold queue, which an automated dialing device will typically classify as an answering machine. It is noted that although the terms “machine” and “service” are used throughout this disclosure, the two terms are used interchangeably to represent a call initially reaching something besides a live party. Thus, traditional automated dialing devices normally screen out almost all calls placed to businesses from ever reaching an agent. As a result, the use of an automated dialing device loses a large portion of its value in a B2B environment and contact centers making such calls must typically resort to using less productive modes for making calls to businesses such as preview dialing and/or manual dialing. With that said, agents placing calls to businesses using preview dialing and/or manual dialing often spend over seventy percent of their time throughout the day trying to reach a live party (right party contact) with the vast majority of agents' time spent listening to and navigating auto attendants and/or voice mail messages, and in many cases waiting on hold for an operator.
Furthermore, calls connecting to phone numbers on wireless networks can often result in garbled audio or signals with excessive noise on the line, gaps of silence between the call being answered by the network and a voice mail greeting playing, and other issues inherent to wireless and cellular networks. Such issues can make it difficult for standard call progress analysis (“CPA”) algorithms to accurately determine if a call has been answered by a live person, a voice mail system, or not at all. In many cases a dialing system may determine a call to a wireless number has reached an answering machine and begin playing a prerecorded message prematurely due to long pauses during the carrier greeting. Overall, CPA accuracy for wireless numbers is currently far lower than it is for traditional land lines, and as wireless phone usage continues to increase around the world, this lack of accuracy will continue to hinder performance and efficiency for countless businesses.
Thus, a need in the art exists for augmenting the call progress analysis performed by automated dialing devices to better handle B2B and wireless dialing environments. More specifically, a need in the art exists for augmenting the call progress analysis performed by automated dialing devices to recognize different machines/services used by businesses and wireless networks to answer calls. Furthermore, a need in the art exists to enable automated dialing devices to negotiate with such machines/services to help call progression once it has been determined a machine or service has answered a call. It is with respect to these considerations and others that the disclosure herein is presented.